Workload has been described both objectively (e.g., number of prescriptions dispensed per pharmacist) as well as subjectively (e.g., pharmacist’s perception of busyness). These approaches might be missing important characteristics of pharmacist workload that have not been previously identified and measured.

Objectives

To measure the association of community pharmacists’ workload perceptions at three levels (organization, job, and task) with job satisfaction, burnout, and perceived performance of two tasks in the medication dispensing process.

Methods

A secondary data analysis was performed using cross-sectional survey data collected from Wisconsin (US) community pharmacists. Organization–related workload was measured as staffing adequacy; job-related workload was measured as general and specific job demands; task-related workload was measured as internal and external mental demands. Pharmacists’ perceived task performance was assessed for patient profile review and patient consultation. The survey was administered to a random sample of 500 pharmacists who were asked to opt in if they were a community pharmacist. Descriptive statistics and correlations of study variables were determined. Two structural equation models were estimated to examine relationships between the study variables and perceived task performance.

Results

From the 224 eligible community pharmacists that agreed to participate, 165 (73.7%) usable surveys were completed and returned. Job satisfaction and job-related monitoring demands had direct positive associations with both dispensing tasks. External task demands were negatively related to perceived patient consultation performance. Indirect effects on both tasks were primarily mediated through job satisfaction, which was positively related to staffing adequacy and cognitive job demands and negatively related to volume job demands. External task demands had an additional indirect effect on perceived patient consultation performance, as it was associated with lower levels of job satisfaction and higher levels of burnout.

Implications/Conclusions

Allowing community pharmacists to concentrate on tasks and limiting interruptions while performing these tasks are important factors in improving quality of patient care and pharmacist work life. The results have implications for strategies to improve patient safety and pharmacist performance.

Nursing workload is increasingly thought to contribute to both nurses’ quality of working life and quality/safety of care. Prior studies lack a coherent model for conceptualizing and measuring the effects of workload in health care. In contrast, we conceptualized a human factors model for workload specifying workload at three distinct levels of analysis and having multiple nurse and patient outcomes.

Methods

To test this model, we analyzed results from a cross-sectional survey of a volunteer sample of nurses in six units of two academic tertiary care pediatric hospitals.

The human factors engineering model of nursing workload was supported by data from two pediatric hospitals. The findings provided a novel insight into specific ways that different types of workload could affect nurse and patient outcomes. These findings suggest further research and yield a number of human factors design suggestions.

Long working hours and sleep deprivation have been a facet of physician training in the US since the advent of the modern residency system. However, the scientific evidence linking fatigue with deficits in human performance, accidents and errors in industries from aeronautics to medicine, nuclear power, and transportation has mounted over the last 40 years. This evidence has also spawned regulations to help ensure public safety across safety-sensitive industries, with the notable exception of medicine.

In late 2007, at the behest of the US Congress, the Institute of Medicine embarked on a year-long examination of the scientific evidence linking resident physician sleep deprivation with clinical performance deficits and medical errors. The Institute of Medicine’s report, entitled “Resident duty hours: Enhancing sleep, supervision and safety”, published in January 2009, recommended new limits on resident physician work hours and workload, increased supervision, a heightened focus on resident physician safety, training in structured handovers and quality improvement, more rigorous external oversight of work hours and other aspects of residency training, and the identification of expanded funding sources necessary to implement the recommended reforms successfully and protect the public and resident physicians themselves from preventable harm.

Given that resident physicians comprise almost a quarter of all physicians who work in hospitals, and that taxpayers, through Medicare and Medicaid, fund graduate medical education, the public has a deep investment in physician training. Patients expect to receive safe, high-quality care in the nation’s teaching hospitals. Because it is their safety that is at issue, their voices should be central in policy decisions affecting patient safety. It is likewise important to integrate the perspectives of resident physicians, policy makers, and other constituencies in designing new policies. However, since its release, discussion of the Institute of Medicine report has been largely confined to the medical education community, led by the Accreditation Council for Graduate Medical Education (ACGME).

To begin gathering these perspectives and developing a plan to implement safer work hours for resident physicians, a conference entitled “Enhancing sleep, supervision and safety: What will it take to implement the Institute of Medicine recommendations?” was held at Harvard Medical School on June 17–18, 2010. This White Paper is a product of a diverse group of 26 representative stakeholders bringing relevant new information and innovative practices to bear on a critical patient safety problem. Given that our conference included experts from across disciplines with diverse perspectives and interests, not every recommendation was endorsed by each invited conference participant. However, every recommendation made here was endorsed by the majority of the group, and many were endorsed unanimously. Conference members participated in the process, reviewed the final product, and provided input before publication. Participants provided their individual perspectives, which do not necessarily represent the formal views of any organization.

In September 2010 the ACGME issued new rules to go into effect on July 1, 2011. Unfortunately, they stop considerably short of the Institute of Medicine’s recommendations and those endorsed by this conference. In particular, the ACGME only applied the limitation of 16 hours to first-year resident physicans. Thus, it is clear that policymakers, hospital administrators, and residency program directors who wish to implement safer health care systems must go far beyond what the ACGME will require. We hope this White Paper will serve as a guide and provide encouragement for that effort.

Resident physician workload and supervision

By the end of training, a resident physician should be able to practice independently. Yet much of resident physicians’ time is dominated by tasks with little educational value. The caseload can be so great that inadequate reflective time is left for learning based on clinical experiences. In addition, supervision is often vaguely defined and discontinuous. Medical malpractice data indicate that resident physicians are frequently named in lawsuits, most often for lack of supervision. The recommendations are:
The ACGME should adjust resident physicians workload requirements to optimize educational value. Resident physicians as well as faculty should be involved in work redesign that eliminates nonessential and noneducational activity from resident physician dutiesMechanisms should be developed for identifying in real time when a resident physician’s workload is excessive, and processes developed to activate additional providersTeamwork should be actively encouraged in delivery of patient care. Historically, much of medical training has focused on individual knowledge, skills, and responsibility. As health care delivery has become more complex, it will be essential to train resident and attending physicians in effective teamwork that emphasizes collective responsibility for patient care and recognizes the signs, both individual and systemic, of a schedule and working conditions that are too demanding to be safeHospitals should embrace the opportunities that resident physician training redesign offers. Hospitals should recognize and act on the potential benefits of work redesign, eg, increased efficiency, reduced costs, improved quality of care, and resident physician and attending job satisfactionAttending physicians should supervise all hospital admissions. Resident physicians should directly discuss all admissions with attending physicians. Attending physicians should be both cognizant of and have input into the care patients are to receive upon admission to the hospitalInhouse supervision should be required for all critical care services, including emergency rooms, intensive care units, and trauma services. Resident physicians should not be left unsupervised to care for critically ill patients. In settings in which the acuity is high, physicians who have completed residency should provide direct supervision for resident physicians. Supervising physicians should always be physically in the hospital for supervision of resident physicians who care for critically ill patientsThe ACGME should explicitly define “good” supervision by specialty and by year of training. Explicit requirements for intensity and level of training for supervision of specific clinical scenarios should be providedCenters for Medicare and Medicaid Services (CMS) should use graduate medical education funding to provide incentives to programs with proven, effective levels of supervision. Although this action would require federal legislation, reimbursement rules would help to ensure that hospitals pay attention to the importance of good supervision and require it from their training programs

Resident physician work hours

Although the IOM “Sleep, supervision and safety” report provides a comprehensive review and discussion of all aspects of graduate medical education training, the report’s focal point is its recommendations regarding the hours that resident physicians are currently required to work. A considerable body of scientific evidence, much of it cited by the Institute of Medicine report, describes deteriorating performance in fatigued humans, as well as specific studies on resident physician fatigue and preventable medical errors.

The question before this conference was what work redesign and cultural changes are needed to reform work hours as recommended by the Institute of Medicine’s evidence-based report? Extensive scientific data demonstrate that shifts exceeding 12–16 hours without sleep are unsafe. Several principles should be followed in efforts to reduce consecutive hours below this level and achieve safer work schedules. The recommendations are:
Limit resident physician work hours to 12–16 hour maximum shiftsA minimum of 10 hours off duty should be scheduled between shiftsResident physician input into work redesign should be actively solicitedSchedules should be designed that adhere to principles of sleep and circadian science; this includes careful consideration of the effects of multiple consecutive night shifts, and provision of adequate time off after night work, as specified in the IOM reportResident physicians should not be scheduled up to the maximum permissible limits; emergencies frequently occur that require resident physicians to stay longer than their scheduled shifts, and this should be anticipated in scheduling resident physicians’ work shiftsHospitals should anticipate the need for iterative improvement as new schedules are initiated; be prepared to learn from the initial phase-in, and change the plan as neededAs resident physician work hours are redesigned, attending physicians should also be considered; a potential consequence of resident physician work hour reduction and increased supervisory requirements may be an increase in work for attending physicians; this should be carefully monitored, and adjustments to attending physician work schedules made as needed to prevent unsafe work hours or working conditions for this group“Home call” should be brought under the overall limits of working hours; work load and hours should be monitored in each residency program to ensure that resident physicians and fellows on home call are getting sufficient sleepMedicare funding for graduate medical education in each hospital should be linked with adherence to the Institute of Medicine limits on resident physician work hours

Moonlighting by resident physicians

The Institute of Medicine report recommended including external as well as internal moonlighting in working hour limits. The recommendation is:
All moonlighting work hours should be included in the ACGME working hour limits and actively monitored. Hospitals should formalize a moonlighting policy and establish systems for actively monitoring resident physician moonlighting

Safety of resident physicians

The “Sleep, supervision and safety” report also addresses fatigue-related harm done to resident physicians themselves. The report focuses on two main sources of physical injury to resident physicians impaired by fatigue, ie, needle-stick exposure to blood-borne pathogens and motor vehicle crashes. Providing safe transportation home for resident physicians is a logistical and financial challenge for hospitals. Educating physicians at all levels on the dangers of fatigue is clearly required to change driving behavior so that safe hospital-funded transport home is used effectively.
Fatigue-related injury prevention (including not driving while drowsy) should be taught in medical school and during residency, and reinforced with attending physicians; hospitals and residency programs must be informed that resident physicians’ ability to judge their own level of impairment is impaired when they are sleep deprived; hence, leaving decisions about the capacity to drive to impaired resident physicians is not recommendedHospitals should provide transportation to all resident physicians who report feeling too tired to drive safely; in addition, although consecutive work should not exceed 16 hours, hospitals should provide transportation for all resident physicians who, because of unforeseen reasons or emergencies, work for longer than consecutive 24 hours; transportation under these circumstances should be automatically provided to house staff, and should not rely on self-identification or request

Training in effective handovers and quality improvement

Handover practice for resident physicians, attendings, and other health care providers has long been identified as a weak link in patient safety throughout health care settings. Policies to improve handovers of care must be tailored to fit the appropriate clinical scenario, recognizing that information overload can also be a problem. At the heart of improving handovers is the organizational effort to improve quality, an effort in which resident physicians have typically been insufficiently engaged. The recommendations are:
Hospitals should train attending and resident physicians in effective handovers of careHospitals should create uniform processes for handovers that are tailored to meet each clinical setting; all handovers should be done verbally and face-to-face, but should also utilize written toolsWhen possible, hospitals should integrate hand-over tools into their electronic medical records (EMR) systems; these systems should be standardized to the extent possible across residency programs in a hospital, but may be tailored to the needs of specific programs and services; federal government should help subsidize adoption of electronic medical records by hospitals to improve signoutWhen feasible, handovers should be a team effort including nurses, patients, and familiesHospitals should include residents in their quality improvement and patient safety efforts; the ACGME should specify in their core competency requirements that resident physicians work on quality improvement projects; likewise, the Joint Commission should require that resident physicians be included in quality improvement and patient safety programs at teaching hospitals; hospital administrators and residency program directors should create opportunities for resident physicians to become involved in ongoing quality improvement projects and root cause analysis teams; feedback on successful quality improvement interventions should be shared with resident physicians and broadly disseminatedQuality improvement/patient safety concepts should be integral to the medical school curriculum; medical school deans should elevate the topics of patient safety, quality improvement, and teamwork; these concepts should be integrated throughout the medical school curriculum and reinforced throughout residency; mastery of these concepts by medical students should be tested on the United States Medical Licensing Examination (USMLE) stepsFederal government should support involvement of resident physicians in quality improvement efforts; initiatives to improve quality by including resident physicians in quality improvement projects should be financially supported by the Department of Health and Human Services

Monitoring and oversight of the ACGME

While the ACGME is a key stakeholder in residency training, external voices are essential to ensure that public interests are heard in the development and monitoring of standards. Consequently, the Institute of Medicine report recommended external oversight and monitoring through the Joint Commission and Centers for Medicare and Medicaid Services (CMS). The recommendations are:
Make comprehensive fatigue management a Joint Commission National Patient Safety Goal; fatigue is a safety concern not only for resident physicians, but also for nurses, attending physicians, and other health care workers; the Joint Commission should seek to ensure that all health care workers, not just resident physicians, are working as safely as possibleFederal government, including the Centers for Medicare and Medicaid Services and the Agency for Healthcare Research and Quality, should encourage development of comprehensive fatigue management programs which all health systems would eventually be required to implementMake ACGME compliance with working hours a “ condition of participation” for reimbursement of direct and indirect graduate medical education costs; financial incentives will greatly increase the adoption of and compliance with ACGME standards

Future financial support for implementation

The Institute of Medicine’s report estimates that $1.7 billion (in 2008 dollars) would be needed to implement its recommendations. Twenty-five percent of that amount ($376 million) will be required just to bring hospitals into compliance with the existing 2003 ACGME rules. Downstream savings to the health care system could potentially result from safer care, but these benefits typically do not accrue to hospitals and residency programs, who have been asked historically to bear the burden of residency reform costs. The recommendations are:
The Institute of Medicine should convene a panel of stakeholders, including private and public funders of health care and graduate medical education, to lay down the concrete steps necessary to identify and allocate the resources needed to implement the recommendations contained in the IOM “Resident duty hours: Enhancing sleep, supervision and safety” report. Conference participants suggested several approaches to engage public and private support for this initiativeEfforts to find additional funding to implement the Institute of Medicine recommendations should focus more broadly on patient safety and health care delivery reform; policy efforts focused narrowly upon resident physician work hours are less likely to succeed than broad patient safety initiatives that include residency redesign as a key componentHospitals should view the Institute of Medicine recommendations as an opportunity to begin resident physician work redesign projects as the core of a business model that embraces safety and ultimately saves resourcesBoth the Secretary of Health and Human Services and the Director of the Centers for Medicare and Medicaid Services should take the Institute of Medicine recommendations into consideration when promulgating rules for innovation grantsThe National Health Care Workforce Commission should consider the Institute of Medicine recommendations when analyzing the nation’s physician workforce needs

Recommendations for future research

Conference participants concurred that convening the stakeholders and agreeing on a research agenda was key. Some observed that some sectors within the medical education community have been reluctant to act on the data. Several logical funders for future research were identified. But above all agencies, Centers for Medicare and Medicaid Services is the only stakeholder that funds graduate medical education upstream and will reap savings downstream if preventable medical errors are reduced as a result of reform of resident physician work hours.

Pediatricians’ workload is increasingly thought to affect pediatricians’ quality of work life and patient safety. Workflow interruptions are a frequent stressor in clinical work, impeding clinicians’ attention and contributing to clinical malpractice. We aimed to investigate prospective associations of workflow interruptions with multiple dimensions of mental workload in pediatricians during clinical day shifts.

Methods

In an Academic Children’s Hospital a prospective study of 28 full shift observations was conducted among pediatricians providing ward coverage. The prevalence of workflow interruptions was based on expert observation using a validated observation instrument. Concurrently, Pediatricians’ workload ratings were assessed with three workload dimensions of the well-validated NASA-Task Load Index: mental demands, effort, and frustration.

Results

Observed pediatricians were, on average, disrupted 4.7 times per hour. Most frequent were interruptions by colleagues (30.2%), nursing staff (29.7%), and by telephone/beeper calls (16.3%). Interruption measures were correlated with two workload outcomes of interest: frequent workflow interruptions were related to less cognitive demands, but frequent interruptions were associated with increased frustration. With regard to single sources, interruptions by colleagues showed the strongest associations to workload.

Conclusions

The findings provide insights into specific pathways between different types of interruptions and pediatricians’ mental workload. These findings suggest further research and yield a number of work and organization re-design suggestions for pediatric care.

Several instruments have been developed to assess psychosocial workload. We compared two of these instruments, the Effort-Reward Imbalance (ERI) model and the Copenhagen Psychosocial Questionnaire (COPSOQ) with regard to congruent validity and internal validity.

Methods

This analysis is based on a population-based sample of the baseline examination of 2,783 employees from the Gutenberg Health Study (GHS). About half of the participants completed the ERI questionnaire (n = 1,342), the other half completed the COPSOQ (n = 1,441). First, the two samples were compared and descriptive analyses were carried out calculating mean values for both instruments in general, then separately for age, gender and main occupational groups. Second, we analyzed the relationship between ERI and COPSOQ scales on the workplace situation and on the workplace outcomes: job satisfaction, general health, burnout, satisfaction with life, by applying stepwise logistic regression analysis.

Results and discussion

For the majority of occupations, high effort as reflected by the ERI corresponded with high demands as reflected by the COPSOQ. Comparably, high reward (according to ERI) yielded a good agreement with high “influence and development” (according to COPSOQ). However, we could also find differences between ERI and COPSOQ concerning the intensity of psychosocial workload in some occupations (e.g., physicians/pharmacists or warehouse managers/warehousemen/transport workers). These differences point to differing theoretical concepts of ERI and COPSOQ. When the ability of ERI and COPSOQ was examined to determine the associations with health and work outcomes, burnout could be better predicted by the COPSOQ; this might be due to the fact that COPSOQ comprises the constructs “work-privacy conflict” and “emotional demand”, which are closely related to burnout. However, methodological differences between these instruments limit their direct comparability.

Conclusions

The ERI and COPSOQ instrument yielded similar results for most occupational groups. The slightly stronger association between psychosocial workload as assessed by COPSOQ and burnout might be explained by its broader approach. The ability of the ERI and COPSOQ instrument to reflect relevant risk factors for clinically manifest disorders (e.g., coronary heart disease) will be derived from subsequent prospective analyses of the GHS with the follow-up data.

The potential for unsafe acts to result in harm to patients is constant risks to be managed in any health care delivery system including pharmacies. The number of reported errors is influenced by a various elements including safety culture. The aim of this study is to investigate a possible relationship between reported dispensing errors and safety culture, taking into account demographic and pharmacy variables, in Swedish community pharmacies.

Methods

A cross-sectional study was performed, encompassing 546 (62.8%) of the 870 Swedish community pharmacies. All staff in the pharmacies on December 1st, 2007 were included in the study. To assess safety culture domains in the pharmacies, the Safety Attitudes Questionnaire (SAQ) was used. Numbers of dispensed prescription items as well as dispensing errors for each pharmacy across the first half year of 2008 were summarised. Intercorrelations among a number of variables including SAQ survey domains, general properties of the pharmacy, demographic characteristics, and dispensing errors were calculated. A negative binomial regression model was used to further examine the relationship between the variables and dispensing errors.

Results

The first analysis demonstrated a number of significant correlations between reported dispensing errors and the variables examined. Negative correlations were found with SAQ domains Teamwork Climate, Safety Climate, Job Satisfaction as well as mean age and response rates. Positive relationships were demonstrated with Stress Recognition (SAQ), number of employees, educational diversity, birth country diversity, education country diversity and number of dispensed prescription items. Variables displaying a significant relationship to errors in this analysis were included in the regression analysis. When controlling for demographic variables, only Stress Recognition, mean age, educational diversity and number of dispensed prescription items and employees, were still associated with dispensing errors.

Conclusion

This study replicated previous work linking safety to errors, but went one step further and controlled for a variety of variables. Controlling rendered the relationship between Safety Climate and dispensing insignificant, while the relationship to Stress Recognition remained significant. Variables such as age and education country diversity were found also to correlate with reporting behaviour. Further studies on the demographic variables might generate interesting results.

As health care workers face a wide range of psychosocial stressors, they are at a high risk of developing burnout syndrome, which in turn may affect hospital outcomes such as the quality and safety of provided care. The purpose of the present study was to investigate the moderating effect of job control on the relationship between workload and burnout.

Methods

A total of 352 hospital workers from five Italian public hospitals completed a self-administered questionnaire that was used to measure exhaustion, cynicism, job control, and workload. Data were collected in 2013.

Results

In contrast to previous studies, the results of this study supported the moderation effect of job control on the relationship between workload and exhaustion. Furthermore, the results found support for the sequential link from exhaustion to cynicism.

Conclusion

This study showed the importance for hospital managers to carry out management practices that promote job control and provide employees with job resources, in order to reduce the burnout risk.

1836 persons died during the follow-up. Low job control among men increased (age-adjusted HR 1.26, 95% CI 1.12 to 1.42) and high job demand among women decreased the risk for total mortality HR 0.82 (95% CI 0.71 to 0.95). Adjustment for occupational group, lifestyle and health factors attenuated the association for men. In the analyses stratified by occupational group, high job strain increased the risk of mortality among white-collar men (HR 1.52, 95% CI 1.09 to 2.13) and passive job among blue-collar men (HR 1.28, 95% CI 1.05 to 1.47) compared with men with low job strain. Adjustment for lifestyle and health factors attenuated the risks. Among white-collar women having an active job decreased the risk for mortality (HR 0.78, 95% CI 0.60 to 1.00).

Conclusion

The impact of job strain on mortality was different according to gender and occupational group among middle-aged public sector employees.

Article summary

Article focus

High job strain and its components, high job demand and low job control, predict cardiovascular and total mortality.

Although lower socioeconomic position is a risk factor for premature total mortality, few studies have explored the effect of job strain on mortality within socioeconomic groups and the ones that exist, report conflicting findings.

Key messages

In a population-based cohort of middle-aged public sector employees, low job control among men increased and high job demand among women decreased the risk of mortality during a 28-year follow-up.

High job strain increased the risk of mortality among white-collar men and passive job among blue-collar men compared with men with low job strain.

Active job among white-collar women decreased the risk for mortality compared with those with low job strain.

Strengths and limitations of this study

A major strength was the representative large sample of public sector employees working both in white-collar and blue-collar professions and the long follow-up time on mortality collected from the national mortality register.

A limitation is the self-reported job strain, however, high correlations between subjective and expert ratings on work conditions have been reported. The assessment of job strain was measured at a single time point in midlife which might imperfectly reflect long-term job strain, however, the municipal employees in our cohort had stable work histories indicating stability probably also for job strain during their earlier working life.

Burnout is a state of mental and physical exhaustion related to work or care giving activities. Burnout during residency training has gained significant attention secondary to concerns regarding job performance and patient care. This article reviews the relevant literature on burnout in order to provide information to educators about its prevalence, features, impact, and potential interventions.

Methods

Studies were identified through a Medline and PsychInfo search from 1974 to 2009. Fifty-one studies were identified. Definition and description of burnout and measurement methods are presented followed by a thorough review of the studies.

Results

An examination of the burnout literature reveals that it is prevalent in medical students (28%–45%), residents (27%–75%, depending on specialty), as well as practicing physicians. Psychological distress and physical symptoms can impact work performance and patient safety. Distress during medical school can lead to burnout, which in turn can result in negative consequences as a working physician. Burnout also poses significant challenges during early training years in residency. Time demands, lack of control, work planning, work organization, inherently difficult job situations, and interpersonal relationships, are considered factors contributing to residents' burnout. Potential interventions include workplace-driven and individual-driven measures. Workplace interventions include education about burnout, workload modifications, increasing the diversity of work duties, stress management training, mentoring, emotional intelligence training, and wellness workshops. Individual-driven behavioral, social, and physical activities include promoting interpersonal professional relations, meditation, counseling, and exercise.

Conclusions

Educators need to develop an active awareness of burnout and ought to consider incorporating relevant instruction and interventions during the process of training resident physicians.

Frontline employees in the helping professions often perform their duties against a difficult backdrop, including a complex client base and ongoing themes of crisis, suffering, and distress. These factors combine to create an environment in which workers are vulnerable to workplace stress and burnout. The present study tested two models to understand how frontline workers in the homelessness sector deal with the suffering of their clients. First, we examined whether relationships between suffering and workplace functioning (job satisfaction and burnout) would be mediated by organizational identification. Second, we examined whether emotional distance from clients (i.e., infrahumanization, measured as reduced attribution of secondary emotions) would predict improved workplace functioning (less burnout and greater job satisfaction), particularly when client contact is high. The study involved a mixed-methods design comprising interview (N = 26) and cross-sectional survey data (N = 60) with a sample of frontline staff working in the homelessness sector. Participants were asked to rate the level of client suffering and attribute emotions in a hypothetical client task, and to complete questionnaire measures of burnout, job satisfaction, and organizational identification. We found no relationships between secondary emotion attribution and burnout or satisfaction. Instead, we found that perceiving higher client suffering was linked with higher job satisfaction and lower burnout. Mediation analyses revealed a mediating role for identification, such that recognizing suffering predicted greater identification with the organization, which fully mediated the relationship between suffering and job satisfaction, and also between suffering and burnout. Qualitative analysis of interview data also resonated with this conceptualization. We introduce this novel finding as the ‘Florence Nightingale effect’. With this sample drawn from the homelessness sector, we provide preliminary evidence for the proposition that recognizing others’ suffering may serve to increase job satisfaction and reduce burnout – by galvanizing organizational identification.

The associations between socioeconomic status (SES), physical and psychosocial workload and health are well documented. According to The Cognitive Activation Theory of Stress (CATS), learned response outcome expectancies (coping, helplessness, and hopelessness) are also important contributors to health. This is in part as independent factors for health, but coping may also function as a buffer against the impact different demands have on health.

Purpose

The purpose of this study was to investigate the relative effect of SES (as measured by level of education), physical workload, and response outcome expectancies on subjective health complaints (SHC) and self-rated health, and if response outcome expectancies mediate the effects of education and physical workload on SHC and self-rated health.

Methods

A survey was carried out among 1,746 Norwegian municipal employees (mean age 44.2, 81 % females). Structural Equation Models with SHC and self-rated health as outcomes were conducted. Education, physical workload, and response outcome expectancies, were the independent 28 variables in the model.

Results

Helplessness/hopelessness had a stronger direct effect on self-rated health and SHC than education and physical workload, for both men and women. Helplessness/hopelessness fully mediated the effect of physical workload on SHC for men (0.121), and mediated 30 % of a total effect of 0.247 for women. For women, education had a small but significant indirect effect through helplessness/hopelessness on self-rated health (0.040) and SHC (−0.040), but no direct effects were found. For men, there was no effect of education on SHC, and only a direct effect on self-rated health (0.134).

Conclusions

The results indicated that helplessness/hopelessness is more important for SHC and health than well-established measures on SES such as years of education and perceived physical workload in this sample. Helplessness/hopelessness seems to function as a mechanism between physical workload and health.

There are many stress factors in occupational settings, and the lack of vacations could be one of factors in the context of work stress. The authors have been studying the relationship between workload and employee health. This time, an investigation into the effects of leisure vacations on worker health status using male white-collar employees aged 20–60 years engaged in a manufacturing company was conducted. The subjects were questioned on work stress factors including vacations and modifiers in their occupational settings, and on psychological and physiological stress reactions; that is, how often they were able to take leisure vacations every year, their average working hours a day and work stress factors from the Demand-Control-Support model. The questions also examined other factors concerning the employees such as type-A behavior and lifestyles as modifiers, diseases of the employees, physical complaints, feelings about sleep, perceived stress, job and life satisfaction, and stress reactions as measured by physiological examination. Correlation and logistic regression analysis were conducted with the 551 eligible subjects. The results were as follows: Leisure vacation was decreasingly related to some of psychological stress reactions after adjustment was made for working hours and for modifiers. Less vacation was increasingly related to the workers’ diseases especially among the employees aged 20–34, though the association was not statistically significant. Vacations did not show obvious association with physiological measures. These findings demonstrate the effectiveness and possibility of leisure vacation in controlling fatigue and maintaining the health of workers. Vacation should always be taken into consideration as a stress factor in a survey of the health problems of white-collar workers.

This study was undertaken to improve the performance of a Chemotherapy Treatment Unit by increasing the throughput and reducing the average patient’s waiting time. In order to achieve this objective, a scheduling template has been built. The scheduling template is a simple tool that can be used to schedule patients' arrival to the clinic. A simulation model of this system was built and several scenarios, that target match the arrival pattern of the patients and resources availability, were designed and evaluated. After performing detailed analysis, one scenario provide the best system’s performance. A scheduling template has been developed based on this scenario. After implementing the new scheduling template, 22.5% more patients can be served.

Introduction

CancerCare Manitoba is a provincially mandated cancer care agency. It is dedicated to provide quality care to those who have been diagnosed and are living with cancer. MacCharles Chemotherapy unit is specially built to provide chemotherapy treatment to the cancer patients of Winnipeg. In order to maintain an excellent service, it tries to ensure that patients get their treatment in a timely manner. It is challenging to maintain that goal because of the lack of a proper roster, the workload distribution and inefficient resource allotment. In order to maintain the satisfaction of the patients and the healthcare providers, by serving the maximum number of patients in a timely manner, it is necessary to develop an efficient scheduling template that matches the required demand with the availability of resources. This goal can be reached using simulation modelling. Simulation has proven to be an excellent modelling tool. It can be defined as building computer models that represent real world or hypothetical systems, and hence experimenting with these models to study system behaviour under different scenarios.1, 2

A study was undertaken at the Children's Hospital of Eastern Ontario to identify the issues behind the long waiting time of a emergency room.3 A 20-­‐day field observation revealed that the availability of the staff physician and interaction affects the patient wait time. Jyväskylä et al.4 used simulation to test different process scenarios, allocate resources and perform activity-­‐based cost analysis in the Emergency Department (ED) at the Central Hospital. The simulation also supported the study of a new operational method, named "triage-team" method without interrupting the main system. The proposed triage team method categorises the entire patient according to the urgency to see the doctor and allows the patient to complete the necessary test before being seen by the doctor for the first time. The simulation study showed that it will decrease the throughput time of the patient and reduce the utilisation of the specialist and enable the ordering all the tests the patient needs right after arrival, thus quickening the referral to treatment.

Santibáñez et al.5 developed a discrete event simulation model of British Columbia Cancer Agency"s ambulatory care unit which was used to study the impact of scenarios considering different operational factors (delay in starting clinic), appointment schedule (appointment order, appointment adjustment, add-­‐ons to the schedule) and resource allocation. It was found that the best outcomes were obtained when not one but multiple changes were implemented simultaneously. Sepúlveda et al.6 studied the M. D. Anderson Cancer Centre Orlando, which is a cancer treatment facility and built a simulation model to analyse and improve flow process and increase capacity in the main facility. Different scenarios were considered like, transferring laboratory and pharmacy areas, adding an extra blood draw room and applying different scheduling techniques of patients. The study shows that by increasing the number of short-­‐term (four hours or less) patients in the morning could increase chair utilisation.

Discrete event simulation also helps improve a service where staff are ignorant about the behaviour of the system as a whole; which can also be described as a real professional system. Niranjon et al.7 used simulation successfully where they had to face such constraints and lack of accessible data. Carlos et al. 8 used Total quality management and simulation – animation to improve the quality of the emergency room. Simulation was used to cover the key point of the emergency room and animation was used to indicate the areas of opportunity required. This study revealed that a long waiting time, overload personnel and increasing withdrawal rate of patients are caused by the lack of capacity in the emergency room.

Baesler et al.9 developed a methodology for a cancer treatment facility to find stochastically a global optimum point for the control variables. A simulation model generated the output using a goal programming framework for all the objectives involved in the analysis. Later a genetic algorithm was responsible for performing the search for an improved solution. The control variables that were considered in this research are number of treatment chairs, number of drawing blood nurses, laboratory personnel, and pharmacy personnel. Guo et al. 10 presented a simulation framework considering demand for appointment, patient flow logic, distribution of resources, scheduling rules followed by the scheduler. The objective of the study was to develop a scheduling rule which will ensure that 95% of all the appointment requests should be seen within one week after the request is made to increase the level of patient satisfaction and balance the schedule of each doctor to maintain a fine harmony between "busy clinic" and "quiet clinic".

Huschka et al.11 studied a healthcare system which was about to change their facility layout. In this case a simulation model study helped them to design a new healthcare practice by evaluating the change in layout before implementation. Historical data like the arrival rate of the patients, number of patients visited each day, patient flow logic, was used to build the current system model. Later, different scenarios were designed which measured the changes in the current layout and performance.

Wijewickrama et al.12 developed a simulation model to evaluate appointment schedule (AS) for second time consultations and patient appointment sequence (PSEQ) in a multi-­‐facility system. Five different appointment rule (ARULE) were considered: i) Baily; ii) 3Baily; iii) Individual (Ind); iv) two patients at a time (2AtaTime); v) Variable Interval and (V-­‐I) rule. PSEQ is based on type of patients: Appointment patients (APs) and new patients (NPs). The different PSEQ that were studied in this study were: i) first-­‐ come first-­‐serve; ii) appointment patient at the beginning of the clinic (APBEG); iii) new patient at the beginning of the clinic (NPBEG); iv) assigning appointed and new patients in an alternating manner (ALTER); v) assigning a new patient after every five-­‐appointment patients. Also patient no show (0% and 5%) and patient punctuality (PUNCT) (on-­‐time and 10 minutes early) were also considered. The study found that ALTER-­‐Ind. and ALTER5-­‐Ind. performed best on 0% NOSHOW, on-­‐time PUNCT and 5% NOSHOW, on-­‐time PUNCT situation to reduce WT and IT per patient. As NOSHOW created slack time for waiting patients, their WT tends to reduce while IT increases due to unexpected cancellation. Earliness increases congestion whichin turn increases waiting time.

Ramis et al.13 conducted a study of a Medical Imaging Center (MIC) to build a simulation model which was used to improve the patient journey through an imaging centre by reducing the wait time and making better use of the resources. The simulation model also used a Graphic User Interface (GUI) to provide the parameters of the centre, such as arrival rates, distances, processing times, resources and schedule. The simulation was used to measure the waiting time of the patients in different case scenarios. The study found that assigning a common function to the resource personnel could improve the waiting time of the patients.

The objective of this study is to develop an efficient scheduling template that maximises the number of served patients and minimises the average patient's waiting time at the given resources availability. To accomplish this objective, we will build a simulation model which mimics the working conditions of the clinic. Then we will suggest different scenarios of matching the arrival pattern of the patients with the availability of the resources. Full experiments will be performed to evaluate these scenarios. Hence, a simple and practical scheduling template will be built based on the indentified best scenario. The developed simulation model is described in section 2, which consists of a description of the treatment room, and a description of the types of patients and treatment durations. In section 3, different improvement scenarios are described and their analysis is presented in section 4. Section 5 illustrates a scheduling template based on one of the improvement scenarios. Finally, the conclusion and future direction of our work is exhibited in section 6.

Simulation Model

A simulation model represents the actual system and assists in visualising and evaluating the performance of the system under different scenarios without interrupting the actual system. Building a proper simulation model of a system consists of the following steps.

Observing the system to understand the flow of the entities, key players, availability of resources and overall generic framework.

Collecting the data on the number and type of entities, time consumed by the entities at each step of their journey, and availability of resources.

After building the simulation model it is necessary to confirm that the model is valid. This can be done by confirming that each entity flows as it is supposed to and the statistical data generated by the simulation model is similar to the collected data.

Figure 1 shows the patient flow process in the treatment room. On the patient's first appointment, the oncologist comes up with the treatment plan. The treatment time varies according to the patient’s condition, which may be 1 hour to 10 hours. Based on the type of the treatment, the physician or the clinical clerk books an available treatment chair for that time period.

On the day of the appointment, the patient will wait until the booked chair is free. When the chair is free a nurse from that station comes to the patient, verifies the name and date of birth and takes the patient to a treatment chair. Afterwards, the nurse flushes the chemotherapy drug line to the patient's body which takes about five minutes and sets up the treatment. Then the nurse leaves to serve another patient. Chemotherapy treatment lengths vary from less than an hour to 10 hour infusions. At the end of the treatment, the nurse returns, removes the line and notifies the patient about the next appointment date and time which also takes about five minutes. Most of the patients visit the clinic to take care of their PICC line (a peripherally inserted central catheter). A PICC is a line that is used to inject the patient with the chemical. This PICC line should be regularly cleaned, flushed to maintain patency and the insertion site checked for signs of infection. It takes approximately 10–15 minutes to take care of a PICC line by a nurse.

Cancer Care Manitoba provided access to the electronic scheduling system, also known as "ARIA" which is comprehensive information and image management system that aggregates patient data into a fully-­‐electronic medical chart, provided by VARIAN Medical System. This system was used to find out how many patients are booked in every clinic day. It also reveals which chair is used for how many hours. It was necessary to search a patient's history to find out how long the patient spends on which chair. Collecting the snapshot of each patient gives the complete picture of a one day clinic schedule.

The treatment room consists of the following two main limited resources:

Treatment Chairs: Chairs that are used to seat the patients during the treatment.

Nurses: Nurses are required to inject the treatment line into the patient and remove it at the end of the treatment. They also take care of the patients when they feel uncomfortable.

Mc Charles Chemotherapy unit consists of 11 nurses, and 5 stations with the following description:

Station 1: Station 1 has six chairs (numbered 1 to 6) and two nurses. The two nurses work from 8:00 to 16:00.

Station 2: Station 2 has six chairs (7 to 12) and three nurses. Two nurses work from 8:00 to 16:00 and one nurse works from 12:00 to 20:00.

Station 3: Station 4 has six chairs (13 to 18) and two nurses. The two nurses work from 8:00 to 16:00.

Station 4: Station 4 has six chairs (19 to 24) and three nurses. One nurse works from 8:00 to 16:00. Another nurse works from 10:00 to 18:00.

Solarium Station: Solarium Station has six chairs (Solarium Stretcher 1, Solarium Stretcher 2, Isolation, Isolation emergency, Fire Place 1, Fire Place 2). There is only one nurse assigned to this station that works from 12:00 to 20:00. The nurses from other stations can help when need arises.

There is one more nurse known as the "float nurse" who works from 11:00 to 19:00. This nurse can work at any station. Table 1 summarises the working hours of chairs and nurses. All treatment stations start at 8:00 and continue until the assigned nurse for that station completes her shift.

Currently, the clinic uses a scheduling template to assign the patients' appointments. But due to high demand of patient appointment it is not followed any more. We believe that this template can be improved based on the availability of nurses and chairs. Clinic workload was collected from 21 days of field observation. The current scheduling template has 10 types of appointment time slot: 15-­‐minute, 1-­‐hour, 1.5-­‐hour, 2-­‐hour, 3-­‐hour, 4-­‐hour, 5-­‐hour, 6-­‐hour, 8-­‐hour and 10-­‐hour and it is designed to serve 95 patients. But when the scheduling template was compared with the 21 days observations, it was found that the clinic is serving more patients than it is designed for. Therefore, the providers do not usually follow the scheduling template. Indeed they very often break the time slots to accommodate slots that do not exist in the template. Hence, we find that some of the stations are very busy (mostly station 2) and others are underused. If the scheduling template can be improved, it will be possible to bring more patients to the clinic and reduce their waiting time without adding more resources.

In order to build or develop a simulation model of the existing system, it is necessary to collect the following data:

Types of treatment durations.

Numbers of patients in each treatment type.

Arrival pattern of the patients.

Steps that the patients have to go through in their treatment journey and required time of each step.

Using the observations of 2,155 patients over 21 days of historical data, the types of treatment durations and the number of patients in each type were estimated. This data also assisted in determining the arrival rate and the frequency distribution of the patients. The patients were categorised into six types. The percentage of these types and their associated service times distributions are determined too.

ARENA Rockwell Simulation Software (v13) was used to build the simulation model. Entities of the model were tracked to verify that the patients move as intended. The model was run for 30 replications and statistical data was collected to validate the model. The total number of patients that go though the model was compared with the actual number of served patients during the 21 days of observations.

Improvement Scenarios

After verifying and validating the simulation model, different scenarios were designed and analysed to identify the best scenario that can handle more patients and reduces the average patient's waiting time. Based on the clinic observation and discussion with the healthcare providers, the following constraints have been stated:

The stations are filled up with treatment chairs. Therefore, it is literally impossible to fit any more chairs in the clinic. Moreover, the stakeholders are not interested in adding extra chairs.

The stakeholders and the caregivers are not interested in changing the layout of the treatment room.

Given these constraints the options that can be considered to design alternative scenarios are:

Changing the arrival pattern of the patients: that will fit over the nurses' availability.

Changing the nurses' schedule.

Adding one full time nurse at different starting times of the day.

Figure 2 compares the available number of nurses and the number of patients' arrival during different hours of a day. It can be noticed that there is a rapid growth in the arrival of patients (from 13 to 17) between 8:00 to 10:00 even though the clinic has the equal number of nurses during this time period. At 12:00 there is a sudden drop of patient arrival even though there are more available nurses. It is clear that there is an imbalance in the number of available nurses and the number of patient arrivals over different hours of the day. Consequently, balancing the demand (arrival rate of patients) and resources (available number of nurses) will reduce the patients' waiting time and increases the number of served patients. The alternative scenarios that satisfy the above three constraints are listed in Table 2. These scenarios respect the following rules:

Long treatments (between 4hr to 11hr) have to be scheduled early in the morning to avoid working overtime.

Patients of type 1 (15 minutes to 1hr treatment) are the most common. They can be fitted in at any time of the day because they take short treatment time. Hence, it is recommended to bring these patients in at the middle of the day when there are more nurses.

Nurses get tired at the end of the clinic day. Therefore, fewer patients should be scheduled at the late hours of the day.

In Scenario 1, the arrival pattern of the patient was changed so that it can fit with the nurse schedule. This arrival pattern is shown Table 3. Figure 3 shows the new patients' arrival pattern compared with the current arrival pattern. Similar patterns can be developed for the remaining scenarios too.

Analysis of Results

ARENA Rockwell Simulation software (v13) was used to develop the simulation model. There is no warm-­‐up period because the model simulates day-­‐to-­‐day scenarios. The patients of any day are supposed to be served in the same day. The model was run for 30 days (replications) and statistical data was collected to evaluate each scenario. Tables 4 and 5 show the detailed comparison of the system performance between the current scenario and Scenario 1. The results are quite interesting. The average throughput rate of the system has increased from 103 to 125 patients per day. The maximum throughput rate can reach 135 patients. Although the average waiting time has increased, the utilisation of the treatment station has increased by 15.6%. Similar analysis has been performed for the rest of the other scenarios. Due to the space limitation the detailed results are not given. However, Table 6 exhibits a summary of the results and comparison between the different scenarios. Scenario 1 was able to significantly increase the throughput of the system (by 21%) while it still results in an acceptable low average waiting time (13.4 minutes). In addition, it is worth noting that adding a nurse (Scenarios 3, 4, and 5) does not significantly reduce the average wait time or increase the system's throughput. The reason behind this is that when all the chairs are busy, the nurses have to wait until some patients finish the treatment. As a consequence, the other patients have to wait for the commencement of their treatment too. Therefore, hiring a nurse, without adding more chairs, will not reduce the waiting time or increase the throughput of the system. In this case, the only way to increase the throughput of the system is by adjusting the arrival pattern of patients over the nurses' schedule.

Developing a Scheduling Template based on Scenario 1

Scenario 1 provides the best performance. However a scheduling template is necessary for the care provider to book the patients. Therefore, a brief description is provided below on how scheduling the template is developed based on this scenario.

Table 3 gives the number of patients that arrive hourly, following Scenario 1. The distribution of each type of patient is shown in Table 7. This distribution is based on the percentage of each type of patient from the collected data. For example, in between 8:00-­‐9:00, 12 patients will come where 54.85% are of Type 1, 34.55% are of Type 2, 15.163% are of Type 3, 4.32% are of Type 4, 2.58% are of Type 5 and the rest are of Type 6. It is worth noting that, we assume that the patients of each type arrive as a group at the beginning of the hourly time slot. For example, all of the six patients of Type 1 from 8:00 to 9:00 time slot arrive at 8:00.

The numbers of patients from each type is distributed in such a way that it respects all the constraints described in Section 1.3. Most of the patients of the clinic are from type 1, 2 and 3 and they take less amount of treatment time compared with the patients of other types. Therefore, they are distributed all over the day. Patients of type 4, 5 and 6 take a longer treatment time. Hence, they are scheduled at the beginning of the day to avoid overtime. Because patients of type 4, 5 and 6 come at the beginning of the day, most of type 1 and 2 patients come at mid-­‐day (12:00 to 16:00). Another reason to make the treatment room more crowded in between 12:00 to 16:00 is because the clinic has the maximum number of nurses during this time period. Nurses become tired at the end of the clinic which is a reason not to schedule any patient after 19:00.

Based on the patient arrival schedule and nurse availability a scheduling template is built and shown in Figure 4. In order to build the template, if a nurse is available and there are patients waiting for service, a priority list of these patients will be developed. They are prioritised in a descending order based on their estimated slack time and secondarily based on the shortest service time. The secondary rule is used to break the tie if two patients have the same slack. The slack time is calculated using the following equation:

Slack time = Due time - (Arrival time + Treatment time)

Due time is the clinic closing time. To explain how the process works, assume at hour 8:00 (in between 8:00 to 8:15) two patients in station 1 (one 8-­‐hour and one 15-­‐ minute patient), two patients in station 2 (two 12-­‐hour patients), two patients in station 3 (one 2-­‐hour and one 15-­‐ minute patient) and one patient in station 4 (one 3-­‐hour patient) in total seven patients are scheduled. According to Figure 2, there are seven nurses who are available at 8:00 and it takes 15 minutes to set-­‐up a patient. Therefore, it is not possible to schedule more than seven patients in between 8:00 to 8:15 and the current scheduling is also serving seven patients by this time. The rest of the template can be justified similarly.

Social inequalities in health are widely examined. But the reasons behind this phenomenon still remain unclear in parts. It is undisputed that the work environment plays a crucial role in this regard. However, the contribution of psychosocial factors at work is unclear and inconsistent, and most studies are limited with regard to work factors and health outcomes. This study, therefore, aimed to explore the role and contribution of various physical and psychosocial working conditions to explaining social inequalities in different self-reported health outcomes.

Methods

Data from a postal survey among the workforces of four medium-sized and large companies from diverse industries of the secondary sector in Switzerland were used and analysed. The study sample covered 1,846 employees aged 20 and 64 and included significant proportions of unskilled manual workers and highly qualified non-manual workers. Cross tabulations and logistic regression analyses were performed to study multiple associations between social status, work factors and health outcomes. Combinations of educational level and occupational position wee used as a measure of social status or class.

Results

Clear social gradients were observed for almost all adverse working conditions and poor health outcomes studied, but in different directions. While physical workloads and other typical blue-collar job characteristics not suprisingly, were found to be much more common among the lower classes, most psychosocial work demands and job resources were more prevalent in the higher classes. Furthermore, workers in lower classes, i.e. with lower educational and occupational status, were more likely to report poor self-rated health, limited physical functioning and long sickness absence, but at the same time were less likely to experience increased stress feelings and burnout symptoms showing a reversed health gradient. Finally, blue-collar job characteristics contributed substantially to the social gradient found in general and physical health outcomes. In contrast, white-collar job characteristics made no contribution to explaining the gradient in these health outcomes, but instead largely explained the reversed social gradient observed for the mental health outcomes.

Conclusion

The findings suggest a more differentiated pattern of the commonly found social gradient in health and the differential role of work in this respect.

Most research on the work conditions and family responsibilities associated with work-family conflict and other measures of mental health uses the individual employee as the unit of analysis. We argue that work conditions are both individual psychosocial assessments and objective characteristics of the proximal work environment, necessitating multilevel analyses of both individual- and team-level work conditions on mental health.

We find that work-to-family conflict is socially patterned across teams, as are job satisfaction and emotional exhaustion. Team-level job conditions predict team-level outcomes, while individuals’ perceptions of their job conditions are better predictors of individuals’ work-to-family conflict and mental health. Work-to-family conflict operates as a partial mediator between job demands and mental health outcomes.

Practical implications

Our findings suggest that organizational leaders concerned about presenteeism, sickness absences, and productivity would do well to focus on changing job conditions in ways that reduce job demands and work-to-family conflict in order to promote employees’ mental health.

Originality/value of the chapter

We show that both work-to-family conflict and job conditions can be fruitfully framed as team characteristics, shared appraisals held in common by team members. This challenges the framing of work-to-family conflict as a “private trouble” and provides support for work-to-family conflict as a structural mismatch grounded in the social and temporal organization of work.

The objectives of the study were to investigate job burnout and leader-member exchange (LMX) levels as well as to evaluate buffering effects of LMX on burnout among dietitians and chefs at institutional foodservices. Hypotheses were proposed based on the Job Demands-Resources model and LMX theory. The study population consisted of dietitians and chefs who were in charge of managing unit operations in a nationwide contract management company. Positive/negative affectivity, workload, job burnout, and LMX scales that had been validated in previous research were adopted. A total of 552 questionnaires were distributed and 154 responses were returned. Results indicated that respondents' burnout levels were moderate and emotional exhaustion was greater than cynicism. In terms of LMX, the surveyed dietitians and chefs showed higher respect toward their supervisors than loyalty. When positive affectivity and negative affectivity were controlled, workload influenced emotional exhaustion and professional efficacy significantly. With affectivity and workload controlled, however, LMX did not influence any dimensions of burnout. The moderating effect of LMX on the relationship between workload and cynicism was significant. That is, the effect of workload on cynicism was weak if the dietitians and chefs perceived the relationship with their supervisor positively. Based on the findings and literature reviewed, how to mitigate job burnout among foodservice managers is discussed.

Burnout is a common problem among physicians and physicians-in-training. The Maslach Burnout Inventory (MBI) is the gold standard for burnout assessment, but the length of this well-validated 22-item instrument can limit its feasibility for survey research.

OBJECTIVE

To evaluate the concurrent validity of two questions relative to the full MBI for measuring the association of burnout with published outcomes.

DESIGN, PARTICIPANTS, AND MAIN MEASURES

The single questions “I feel burned out from my work” and “I have become more callous toward people since I took this job,” representing the emotional exhaustion and depersonalization domains of burnout, respectively, were evaluated in published studies of medical students, internal medicine residents, and practicing surgeons. We compared predictive models for the association of each question, versus the full MBI, using longitudinal data on burnout and suicidality from 2006 and 2007 for 858 medical students at five United States medical schools, cross-sectional data on burnout and serious thoughts of dropping out of medical school from 2007 for 2222 medical students at seven United States medical schools, and cross-sectional data on burnout and unprofessional attitudes and behaviors from 2009 for 2566 medical students at seven United States medical schools. We also assessed results for longitudinal data on burnout and perceived major medical errors from 2003 to 2009 for 321 Mayo Clinic Rochester internal medicine residents and cross-sectional data on burnout and both perceived major medical errors and suicidality from 2008 for 7,905 respondents to a national survey of members of the American College of Surgeons.

KEY RESULTS

Point estimates of effect for models based on the single-item measures were uniformly consistent with those reported for models based on the full MBI. The single-item measures of emotional exhaustion and depersonalization exhibited strong associations with each published outcome (all p ≤0.008). No conclusion regarding the relationship between burnout and any outcome variable was altered by the use of the single-item measures rather than the full MBI.

CONCLUSIONS

Relative to the full MBI, single-item measures of emotional exhaustion and depersonalization exhibit strong and consistent associations with key outcomes in medical students, internal medicine residents, and practicing surgeons.

To characterize safety hazards related to e-prescribing in community pharmacies.

Methods

The Sociotechnical Systems (STS) framework was used to investigate the e-prescribing technology interface in community pharmacies by taking into consideration the social, technical and environmental work elements of a user’s interaction with technology. This study focused specifically on aspects of the social subsystem.

Study Design and Setting

The study employed a cross-sectional qualitative design and was conducted in seven community pharmacies in Wisconsin. Direct observations, think aloud protocols, and group interviews were conducted with 14 pharmacists and 16 technicians, and audio-recorded. Recordings were transcribed and subjected to thematic content analysis guided by the sociotechnical systems theoretical framework.

Results

Three major themes that may increase the potential for medication errors with e-prescribing were identified and described. The three themes included: (1) increased cognitive burden on pharmacy staff, such as having to memorize parts of e-prescriptions or having to perform dosage calculations mentally; (2) interruptions during the e-prescription dispensing process; and (3) communication issues with prescribers, patients, and among pharmacy staff. Pharmacy staff reported these consequences of e-prescribing increased the likelihood of medication errors.

Conclusions

This study is the first of its kind to identify patient safety risks related to e-prescribing in community pharmacies using a sociotechnical systems framework. The findings shed light on potential interventions that may enhance patient safety in pharmacies and facilitate improved e-prescribing use. Future studies should confirm patient safety hazards reported and identify ways to utilize e-prescribing effectively and safely in community pharmacies.

Previous research has suggested that personality traits of the Five Factor Model play a role in worker's response to workload. The aim of this study was to investigate the association of personality traits of first responders with their perceived workload in real-life tasks. A flying column of 269 police officers completed a measure of subjective workload (NASA-Task Load Index) after intervention tasks in a major public event. Officers' scores on a measure of Five Factor Model personality traits were obtained from archival data. Linear Mixed Modeling was used to test the direct and interaction effects of personality traits on workload scores once controlling for background variables, task type and workload source (mental, temporal and physical demand of the task, perceived effort, dissatisfaction for the performance and frustration due to the task). All personality traits except extraversion significantly interacted at least with one workload source. Perceived workload in flying column police officers appears to be the result of their personality characteristics interacting with the workload source. The implications of these results for the development of support measures aimed at reducing the impact of workload in this category of workers are discussed.

Aims: To determine whether change in employment status (from fixed term to permanent employment) is followed by changes in work, health, health related behaviours, and sickness absence.

Methods: Prospective cohort study with four year follow up. Data from 4851 (710 male, 4141 female) hospital employees having a fixed term or permanent job contract on entry to the study were collected at baseline and follow up.

Results: At baseline, compared to permanent employees, fixed term employees reported lower levels of workload, job security, and job satisfaction. They also reported greater work ability. All fixed term employees had a lower rate of medically certified sickness absence at baseline. Baseline rate ratios for those who remained fixed term were 0.64 (95% CI 0.55 to 0.75), and were 0.50 (95% CI 0.34 to 0.75) for those who later became permanent. Continuous fixed term employment was not associated with changes in the outcome measures. Change from fixed term to permanent employment was followed by an increase in job security, enduring job satisfaction, and increased medically certified sickness absence (compared to permanent workers rate ratio 0.96 (95% CI 0.80 to 1.16)). Other indicators of work, health, and health related behaviours remained unchanged.

Conclusion: Receiving a permanent job contract after fixed term employment is associated with favourable changes in job security and job satisfaction. The corresponding increase in sickness absence might be due to a reduction in presenteeism and the wearing off of health related selection.

Recent epidemiological research in Europe has reported that two groups of job demands, i.e., challenges and hindrances, are differently associated with work engagement. The purpose of the present study was to replicate the cross-sectional association of workload and time pressure (as a challenge) and role ambiguity (as a hindrance) with work engagement among Japanese employees.

Methods

Between October 2010 and December 2011, a total of 9,134 employees (7,101 men and 1,673 women) from 12 companies in Japan were surveyed using a self-administered questionnaire comprising the Job Content Questionnaire, National Institute for Occupational Safety and Health Generic Job Stress Questionnaire, short 10-item version of the Effort-Reward Imbalance Questionnaire, short nine-item version of the Utrecht Work Engagement Scale, and demographic characteristics. Multilevel regression analyses with a random intercept model were conducted.

Results

After adjusting for demographic characteristics, workload and time pressure showed a positive association with work engagement with a small effect size (standardized coefficient [β] = 0.102, Cohen’s d [d] = 0.240) while role ambiguity showed a negative association with a large effect size (β = −0.429, d = 1.011). After additionally adjusting for job resources (i.e., decision latitude, supervisor support, co-worker support, and extrinsic reward), the effect size of workload and time pressure was not attenuated (β = 0.093, d = 0.234) while that of role ambiguity was attenuated but still medium (β = −0.242, d = 0.609).

Conclusions

Among Japanese employees, challenges such as having higher levels of workload and time pressure may enhance work engagement but hindrances, such as role ambiguity, may reduce it.

Workload has traditionally been measured by using surrogates, such as number of patients admitted or census, but these may not fully represent the complex concept of workload.

Objective

We measured self-reported subjective workload of interns and explored the relationship between subjective workload and possible predictors of it.

Methods

Trained research assistants observed internal medicine interns on call on a general medicine service. Approximately once an hour, the research assistants recorded the self-reported subjective workload of the interns by using Borg's Self-Perceived Exertion Scale, a 6 to 20 scale, and also recorded their own perceptions of the intern's workload. Research assistants continuously recorded the tasks performed by the interns. Interns were surveyed before and after the observation to obtain demographic and census data.

Self-reported subjective workload was not associated with traditional measures of workload. However, receiving sign-out and assuming the care of cross-coverage patients may be related to higher subjective workload in interns. Given the patient safety implications of workload, it is important that the medical education community have tools to evaluate workload and identify contributors to it.

To determine the effect of job insecurity based on repeated measurements on ischemic heart disease (IHD) and on antihypertensive medication.

Methods

The study population consists of 12,559 employees aged 18–59 years of the Danish Work Environment Cohort Study. With an open cohort design, data from up to four representative waves were linked to four registers. Poisson regression with time-dependent covariates was used to estimate the rate ratio (RR) with confidence interval (CI) of perceived job insecurity associated with first-time IHD hospitalization or mortality 1991–2010 (n = 561 cases) and incident dispensing of prescribed antihypertensive medications 1996–2010 (n = 2,402 cases).

Results

Participants with perceived job insecurity filled more antihypertensive prescriptions (age-, gender-, and calendar year-adjusted RR 1.23, 95 % CI 1.12–1.33) and had a borderline significant higher IHD incidence (RR 1.23, 95 % CI 0.98–1.55). In a subanalysis, the risk of antihypertensive medication dispensed was only significant among employees with worries about both unemployment and poor reemployment opportunities. After explorative stratifications by age, gender, and occupational status, perceived job insecurity was associated with more dispensing of antihypertensive medications to participants less than 50 years of age.

Conclusions

In a country with high social security and active labor market policy, employees with the feeling of an insecure job have a modestly increased risk to fill an antihypertensive prescription. Further studies on health risks of job insecurity should consider improved exposure assessment, earlier outcomes such as medication in order to increase statistical power, and identification of vulnerable population groups.

The purpose of this evidence based analysis report is to examine the safety and effectiveness of point-of-care (POC) international normalized ratio (INR) monitoring devices for patients on long-term oral anticoagulation therapy (OAT).

Clinical Need: Target Population and Condition

Long-term OAT is typically required by patients with mechanical heart valves, chronic atrial fibrillation, venous thromboembolism, myocardial infarction, stroke, and/or peripheral arterial occlusion. It is estimated that approximately 1% of the population receives anticoagulation treatment and, by applying this value to Ontario, there are an estimated 132,000 patients on OAT in the province, a figure that is expected to increase with the aging population.

Patients on OAT are regularly monitored and their medications adjusted to ensure that their INR scores remain in the therapeutic range. This can be challenging due to the narrow therapeutic window of warfarin and variation in individual responses. Optimal INR scores depend on the underlying indication for treatment and patient level characteristics, but for most patients the therapeutic range is an INR score of between 2.0 and 3.0.

The current standard of care in Ontario for patients on long-term OAT is laboratory-based INR determination with management carried out by primary care physicians or anticoagulation clinics (ACCs). Patients also regularly visit a hospital or community-based facility to provide a venous blood samples (venipuncture) that are then sent to a laboratory for INR analysis.

Experts, however, have commented that there may be under-utilization of OAT due to patient factors, physician factors, or regional practice variations and that sub-optimal patient management may also occur. There is currently no population-based Ontario data to permit the assessment of patient care, but recent systematic reviews have estimated that less that 50% of patients receive OAT on a routine basis and that patients are in the therapeutic range only 64% of the time.

Overview of POC INR Devices

POC INR devices offer an alternative to laboratory-based testing and venipuncture, enabling INR determination from a fingerstick sample of whole blood. Independent evaluations have shown POC devices to have an acceptable level of precision. They permit INR results to be determined immediately, allowing for more rapid medication adjustments.

POC devices can be used in a variety of settings including physician offices, ACCs, long-term care facilities, pharmacies, or by the patients themselves through self-testing (PST) or self-management (PSM) techniques. With PST, patients measure their INR values and then contact their physician for instructions on dose adjustment, whereas with PSM, patients adjust the medication themselves based on pre-set algorithms. These models are not suitable for all patients and require the identification and education of suitable candidates.

Potential advantages of POC devices include improved convenience to patients, better treatment compliance and satisfaction, more frequent monitoring and fewer thromboembolic and hemorrhagic complications. Potential disadvantages of the device include the tendency to underestimate high INR values and overestimate low INR values, low thromboplastin sensitivity, inability to calculate a mean normal PT, and errors in INR determination in patients with antiphospholipid antibodies with certain instruments. Although treatment satisfaction and quality of life (QoL) may improve with POC INR monitoring, some patients may experience increased anxiety or preoccupation with their disease with these strategies.

Studies where the POC INR results were not used to guide patient management

Method of Review

A search of electronic databases (OVID MEDLINE, MEDLINE In-Process & Other Non-Indexed Citations, EMBASE, The Cochrane Library, and the International Agency for Health Technology Assessment [INAHTA] database) was undertaken to identify evidence published from January 1, 1998 to November 25, 2008. Studies meeting the inclusion criteria were selected from the search results. Reference lists of selected articles were also checked for relevant studies.

Anticoagulation control is measured by the percentage of time INR is within the therapeutic range or by the percentage of INR values in the therapeutic range. Due to the differing methodologies and reporting structures used, it was deemed inappropriate to combine the data and estimate whether the difference between groups would be significant. Instead, the results of individual studies were weighted by the number of person-years of observation and then pooled to calculate a summary measure.

Across most studies, patients in the intervention groups tended to have a higher percentage of time and values in the therapeutic target range in comparison to control patients. When the percentage of time in the therapeutic range was pooled across studies and weighted by the number of person-years of observation, the difference between the intervention and control groups was 4.2% for PSM, 7.2% for PST and 6.1% for POC use by health care practitioners. Overall, intervention patients were in the target range 69% of the time and control patients were in the therapeutic target range 64% of the time leading to an overall difference between groups of roughly 5%.

Major Complications and Deaths

There was no statistically significant difference in the number of major hemorrhagic events between patients managed with POC INR monitoring devices and patients managed with standard laboratory testing (OR =0.74; 95% CI: 0.52- 1.04). This difference was non-significant for all POC strategies (PSM, PST, health care practitioner).

Patients managed with POC INR monitoring devices had significantly fewer thromboembolic events than usual care patients (OR =0.52; 95% CI: 0.37 - 0.74). When divided by POC strategy, PSM resulted in significantly fewer thromboembolic events than usual care (OR =0.46.; 95% CI: 0.29 - 0.72). The observed difference in thromboembolic events for PSM remained significant when the analysis was limited to major thromboembolic events (OR =0.40; 95% CI: 0.17 - 0.93), but was non-significant when the analysis was limited to minor thromboembolic events (OR =0.73; 95% CI: 0.08 - 7.01). PST and GP/Nurse strategies did not result in significant differences in thromboembolic events, however there were only a limited number of studies examining these interventions.

No statistically significant difference was observed in the number of deaths between POC intervention and usual care control groups (OR =0.67; 95% CI: 0.41 - 1.10). This difference was non-significant for all POC strategies. Only one study reported on survival with 10-year survival rate of 76.1% in the usual care control group compared to 84.5% in the PSM group (P=0.05).

Summary Results of Meta-Analyses of Major Complications and Deaths in POC INR Monitoring Studies

Patient Satisfaction and Quality of Life

Quality of life measures were reported in eight studies comparing POC INR monitoring to standard laboratory testing using a variety of measurement tools. It was thus not possible to calculate a quantitative summary measure. The majority of studies reported favourable impacts of POC INR monitoring on QoL and found better treatment satisfaction with POC monitoring. Results from a pre-analysis patient and caregiver focus group conducted in Ontario also indicated improved patient QoL with POC monitoring.

Quality of the Evidence

Studies varied with regard to patient eligibility, baseline patient characteristics, follow-up duration, and withdrawal rates. Differential drop-out rates were observed such that the POC intervention groups tended to have a larger number of patients who withdrew. There was a lack of consistency in the definitions and reporting for OAT control and definitions of adverse events. In most studies, the intervention group received more education on the use of warfarin and performed more frequent INR testing, which may have overestimated the effect of the POC intervention. Patient selection and eligibility criteria were not always fully described and it is likely that the majority of the PST/PSM trials included a highly motivated patient population. Lastly, a large number of trials were also sponsored by industry.

Despite the observed heterogeneity among studies, there was a general consensus in findings that POC INR monitoring devices have beneficial impacts on the risk of thromboembolic events, anticoagulation control and patient satisfaction and QoL (ES Table 2).

Using a 5-year Markov model, the health and economic outcomes associated with four different anticoagulation management approaches were evaluated:

Standard care: consisting of a laboratory test with a venipuncture blood draw for an INR;

Healthcare staff testing: consisting of a test with a POC INR device in a medical clinic comprised of healthcare staff such as pharmacists, nurses, and physicians following protocol to manage OAT;

PST: patient self-testing using a POC INR device and phoning in results to an ACC or family physician; and

PSM: patient self-managing using a POC INR device and self-adjustment of OAT according to a standardized protocol. Patients may also phone in to a medical office for guidance.

The primary analytic perspective was that of the MOHLTC. Only direct medical costs were considered and the time horizon of the model was five years - the serviceable life of a POC device.

From the results of the economic analysis, it was found that POC strategies are cost-effective compared to traditional INR laboratory testing. In particular, the healthcare staff testing strategy can derive potential cost savings from the use of one device for multiple patients. The PSM strategy, however, seems to be the most cost-effective method i.e. patients are more inclined to adjust their INRs more readily (as opposed to allowing INRs to fall out of range).

Considerations for Ontario Health System

Although the use of POC devices continues to diffuse throughout Ontario, not all OAT patients are suitable or have the ability to practice PST/PSM. The use of POC is currently concentrated at the institutional setting, including hospitals, ACCs, long-term care facilities, physician offices and pharmacies, and is much less commonly used at the patient level. It is, however, estimated that 24% of OAT patients (representing approximately 32,000 patients in Ontario), would be suitable candidates for PST/PSM strategies and willing to use a POC device.

There are several barriers to the use and implementation of POC INR monitoring devices, including factors such as lack of physician familiarity with the devices, resistance to changing established laboratory-based methods, lack of an approach for identifying suitable patients and inadequate resources for effective patient education and training. Issues of cost and insufficient reimbursement strategies may also hinder implementation and effective quality assurance programs would need to be developed to ensure that INR measurements are accurate and precise.

Conclusions

For a select group of patients who are highly motivated and trained, PSM resulted in significantly fewer thromboembolic events compared to conventional laboratory-based INR testing. No significant differences were observed for major hemorrhages or all-cause mortality. PST and GP/Nurse use of POC strategies are just as effective as conventional laboratory-based INR testing for thromboembolic events, major hemorrhages, and all-cause mortality. POC strategies may also result in better OAT control as measured by the proportion of time INR is in the therapeutic range and there appears to be beneficial impacts on patient satisfaction and QoL. The use of POC devices should factor in patient suitability, patient education and training, health system constraints, and affordability.

Objectives: Our objective was to estimate the incidence of recent burnout in a large sample of Taiwanese physicians and analyze associations with job related satisfaction and medical malpractice experience.

Methods: We performed a cross-sectional survey. Physicians were asked to fill out a questionnaire that included demographic information, practice characteristics, burnout, medical malpractice experience, job satisfaction, and medical error experience. There are about 2% of total physicians. Physicians who were members of the Taiwan Society of Emergency Medicine, Taiwan Surgical Association, Taiwan Association of Obstetrics and Gynecology, The Taiwan Pediatric Association, and Taiwan Stroke Association, and physicians of two medical centers, three metropolitan hospitals, and two local community hospitals were recruited.

Results: There is high incidence of burnout among Taiwan physicians. In our research, Visiting staff (VS) and residents were more likely to have higher level of burnout of the emotional exhaustion (EE) and depersonalization (DP), and personal accomplishment (PA). There was no difference in burnout types in gender. Married had higher-level burnout in EE. Physicians who were 20~30 years old had higher burnout levels in EE, those 31~40 years old had higher burnout levels in DP, and PA. Physicians who worked in medical centers had a higher rate in EE, DP, and who worked in metropolitan had higher burnout in PA. With specialty-in-training, physicians had higher-level burnout in EE and DP, but lower burnout in PA. Physicians who worked 13-17hr continuously had higher-level burnout in EE. Those with ≥41 times/week of being on call had higher-level burnout in EE and DP. Physicians who had medical malpractice experience had higher-level burnout in EE, DP, and PA. Physicians who were not satisfied with physician-patient relationships had higher-level burnout than those who were satisfied.

Conclusion: Physicians in Taiwan face both burnout and a high risk in medical malpractice. There is high incidence of burnout among Taiwan physicians. This can cause shortages in medical care human resources and affect patient safety. We believe that high burnout in physicians was due to long working hours and several other factors, like mental depression, the evaluation assessment system, hospital culture, patient-physician relationships, and the environment. This is a very important issue on public health that Taiwanese authorities need to deal with.